生成式AI的发展正在改变用户的替代信息搜寻行为模式，促使用户的使用偏好在传统的以人为中介的替代信息搜寻模式和以生成式AI为中介的新型人-机替代搜寻模式之间转变。基于人-人替代搜寻模式与人-机替代搜寻模式存在的问题和差异，文章分别深入剖析影响用户在这两种模式间转移意愿的关键因素，这对于提升信息搜寻效率和优化生成式AI产品具有重要意义。基于 PPM（推-拉-锚定）模型，构建用户的两种转移意愿（人-人替代搜寻向人-机替代搜寻的转移意愿以及人-机替代搜寻向人-人替代搜寻的转移意愿）模型，采用问卷调查的方式分别收集了407份和430份有效样本数据，使用SPSS和AMOS软件进行后续的数据分析和假设检验。研究表明，人-人替代搜寻向人-机替代搜寻的转移意愿受推力因素（信息质量不满意）、拉力因素（交互性、拟人化、可访问性）和锚定因素（个体创新性、转移成本）的综合影响。人-机替代搜寻向人-人替代搜寻的转移意愿受推力因素（服务质量不满意、隐私风险）、拉力因素（信任）和锚定因素（社会支持）的综合影响。

The development of generative AI is changing the user's alternative information search mode, prompting the user's preference to shift between the traditional human-mediated alternative information search mode and the new human-machine alternative search mode mediated by generative AI. Based on the problems and differences between the human-human alternative search mode and the human-machine alternative search mode, this paper provides an in-depth analysis of the key factors affecting the users' willingness to transfer between these two modes, which is of great significance for enhancing the efficiency of information search and optimizing the generative AI products.Based on the PPM (Push-Pull-Mooring) model, two models of users' willingness to transfer (willingness to transfer from human-human alternative search to human-machine alternative search and willingness to transfer from human-machine alternative search to human-human alternative search) were constructed, and the questionnaire survey was used to collect 407 and 430 valid sample data, respectively, and the subsequent data analysis and hypothesis testing were carried out using SPSS and AMOS software. The willingness to transfer human-human surrogate search to human-machine surrogate search is affected by a combination of push factors (dissatisfaction with information quality), pull factors (interactivity, anthropomorphism, accessibility), and anchoring factors (individual innovativeness, transfer costs).The willingness to transfer from human-machine to human-human surrogate search is influenced by a combination of push factors (dissatisfaction with service quality，privacy risk), pull factors (trust), and anchoring factors (social support).